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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Chris Wagner: The role of Eden Radioisotopes in the future of nuclear medicine
Chris Wagner has more than 40 years of experience in nuclear medicine, beginning as a clinical practitioner before moving into leadership roles at companies like Mallinckrodt (now Curium) and Nordion. His knowledge of both the clinical and the manufacturing sides of nuclear medicine laid the groundwork for helping to found Eden Radioisotopes, a start-up venture that intends to make diagnostic and therapeutic raw material medical isotopes like molybdenum-99 and lutetium-177.
Steven E. Aumeier, Bulent Alpay, John C. Lee, A. Ziya Akcasu
Nuclear Science and Engineering | Volume 153 | Number 2 | June 2006 | Pages 101-123
Technical Paper | doi.org/10.13182/NSE06-A2599
Articles are hosted by Taylor and Francis Online.
We present probabilistic techniques that make synergistic use of available process information for diagnosis and detection of component fault manifestation in a multicomponent system. We begin by describing the motivation for using probabilistic techniques for systems diagnostics and then define probabilistic expressions that embody the diagnostics knowledge of interest. We show that a combination of a Bayesian expression with the solution to the Chapman-Kolmogoroff equation contains the diagnostic information of interest while explicitly making use of available process information including plant data or measurements, mathematical system models, and individual component reliability data. Given these probabilistic expressions, we introduce a practical means of obtaining the necessary constituent probability density functions corresponding to feasible component transitions via an adaptive Kalman filtering formulation. To demonstrate the consolidated probabilistic technique, we consider a low-order model of a balance of plant of a boiling water reactor, represented by 11 system variables, 9 component characteristics, and 5 observations. We simulate 5 to 10% degradations in two components subject to 1% signal noise in two different transient events. Our test calculations indicate that the proposed algorithm is able to provide correct fault detection and diagnosis of the faulted components and fault magnitudes, together with a rank-ordered likelihood of the binary faults.